• Title/Summary/Keyword: DACE 모델

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Optimization of Forging Process of Gate Valve using DACE Model (DACE 모델을 이용한 게이트밸브 단조공정의 최적설계화)

  • Oh, Seung-Hwan;Kong, Hyeong-Geol;Kang, Jung-Ho;Park, Young-Chul
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.6 no.1
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    • pp.71-77
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    • 2007
  • In case of the welding process, a conventional production method of gate valve, it has a merit of light weight, but also a demerit of high production cost and an impossibility in mass production due to work by hand. However, in case of the forging process, it has economic merits and can take a mass production process, too. The main focus of this paper is the optimization of preform in the forging process. This paper proposed an optimal design to improve the mechanical efficiency of gate valve made by forging method instead of welding. the optional design is conducted as application of real response model to Kriging model using computer simulation. Also, from verification of the response model with optimized results we were confirmed that the applications of Kriging method to structural optimum design using finite element analysis and equation are useful and reliable.

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Optimization of a Gate Valve using Design of Experiments and the Kriging Based Approximation Model (실험계획법과 크리깅 근사모델에 의한 게이트밸브 최적화)

  • Kang, Jung-Ho;Kang, Jin;Park, Young-Chul
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.14 no.6
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    • pp.125-131
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    • 2005
  • The purpose of this study is an optimization of gate valve made by forging method instead of welding method. In this study, we propose an optimal shape design to improve the mechanical efficiency of gate valve. In order to optimize more efficiently and reliably, the meta-modeling technique has been developed to solve such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Also, we prove reliability of the DACE model's application to gate valve by computer simulations using FEM(Finite Element Method).

Optimization of Butterfly Valve's Disc Using the DACE Model Based on CAE (CAE에 기반한 DACE 모델을 이용한 버터플라이밸브 디스크의 최적설계)

  • Park Young-Chul;Kang Jung-Ho;Lee Jong-Moon;Kang Jin
    • Journal of Ocean Engineering and Technology
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    • v.20 no.3 s.70
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    • pp.96-102
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    • 2006
  • The butterfly valve has been used to control the switch and flux of fluid. While research about the characteristics of butterfly valve fluid have been done, study of the optimum design, considering structural safety, must keep pace with it. Thus, a method is proposed for an optimum butterfly valve. Initially, the stability of the butterfly valve, using FEM and CFD, is evaluated, and a variable is selected using the initial analysis results. Also, the shape optimization design is accomplished using the DACE model. In terms of research results, the experiment satisfied the objective and limitation functions.

Optimization of a Gate Valve using Orthogonal Array and Kriging Model (직교배열표와 크리깅모델을 이용한 게이트밸브의 최적설계)

  • Kang Jin;Lee Jong-Mun;Kang Jung-Ho;Park Hee-Chun;Park Young-Chul
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.8 s.185
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    • pp.119-126
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    • 2006
  • Kriging model is widely used as design DACE(analysis and computer experiments) model in the field of engineering design to accomplish computationally feasible design optimization. In this paper, the optimization of gate valve was performed using Kriging based approximation model. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. In addition, we describe the definition, the prediction function and the algorithm of Kriging method and examine the accuracy of Kriging by using validation method.

A Study on the Robust Design Using Kriging Surrogate Models (크리깅 근사모델을 이용한 강건설계에 관한 연구)

  • Lee, Kwon-Hee;Cho, Yong-Chul;Park, Gyung-Jin
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.870-875
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    • 2004
  • Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

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Selection Method of Global Model and Correlation Coefficients for Kriging Metamodel (크리깅 메타모델의 전역모델과 상관계수 선정 방법)

  • Cho, Su-Kil;Byun, Hyun-Suk;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.8
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    • pp.813-818
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    • 2009
  • Design analysis and computer experiments (DACE) model is widely used to express efficiently nonlinear responses in the field of engineering design. As a DACE model, kriging model can approximately replace a simulation model that is very expensive or highly nonlinear. The kriging model is composed of the summation of a global model and a local model representing deviation from the global model. The local model is determined by correlation coefficient with the pre-sampled points, where the accuracy and robustness of the kriging model depends on the selection of proper correlation coefficients. Therefore, to achieve the robust kriging model, the range of the correlation coefficients is explored with respect to the degrees of the global model. Based on this study we propose the proper orders of the global model and range of parameters to make accurate and robust kriging model.

A study of the correlation coefficients with respect to the degrees of the global models in the kriging metamodel (크리깅 메타모델에서 전역 모델에 따른 상관계수의 연구)

  • Cho, Su-Kil;Lee, Tae-Hee
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.701-705
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    • 2008
  • Design analysis and computer experiments (DACE) model is widely used to express efficiently the nonlinear responses in the field of engineering design. Kriging model, a DACE model, can approximately replace a simulation model that is very expensive or highly nonlinear. The kriging model is composed of the summation of a global model and a local model representing deviation from global model. The local model is determined by correlation coefficient of the pre-sampled points, where determination of the correct correlation coefficient has an effect on accuracy and robustness of the kriging model. Therefore, robustness of the correlation coefficient is explored with respect to degrees of the global model. Then we propose the range of correlation coefficient to make correct and robust kriging model and the influence of the correlation coefficients on the degrees of global model with respect to the nonlinearity of the pre-sampled responses.

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A Global Robust Optimization Using the Kriging Based Approximation Model (크리깅 근사모델을 이용한 전역적 강건최적설계)

  • Park Gyung-Jin;Lee Kwon-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9 s.240
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    • pp.1243-1252
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    • 2005
  • A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

Structural Optimization for LMTT-Mover Using Sequential Kriging Based Approximation Model (순차적 크리깅 근사모델을 이용한 LMTT 이송체의 구조최적설계)

  • Park Hyung Wook;Han Dong Seop;Lee Kwon Hee;Han Geun Jo
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2005.10a
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    • pp.289-295
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    • 2005
  • LMTT (Linear Motor-based Transfer Techn-ology) is a horizontal transfer system for the yard automation This system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) toot consists of stator modules on the rail and shuttle car. In this research, the kriging interpolation method with sequential sampling find the optimum design of mover in LMTT. The design variables are considered as the transverse, longitudinal and wheel beam's thicknesses. The objective function is set up as weight, while the constant function are set up as the stresses generated by four loading conditions. The objective function is set up as weight. The optimum results obtained by the suggested method are compared with those by the GENESIS.

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Generalized Kriging Model for Interpolation and Regression (보간과 회귀를 위한 일반크리깅 모델)

  • Jung Jae Jun;Lee Tae Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.2 s.233
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    • pp.277-283
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    • 2005
  • Kriging model is widely used as design analysis and computer experiment (DACE) model in the field of engineering design to accomplish computationally feasible design optimization. In general, kriging model has been applied to many engineering applications as an interpolation model because it is usually constructed from deterministic simulation responses. However, when the responses include not only global nonlinearity but also numerical error, it is not suitable to use Kriging model that can distort global behavior. In this research, generalized kriging model that can represent both interpolation and regression is proposed. The performances of generalized kriging model are compared with those of interpolating kriging model for numerical function with error of normal distribution type and trigonometric function type. As an application of the proposed approach, the response of a simple dynamic model with numerical integration error is predicted based on sampling data. It is verified that the generalized kriging model can predict a noisy response without distortion of its global behavior. In addition, the influences of maximum likelihood estimation to prediction performance are discussed for the dynamic model.